IBDS Joint Seminar with IDEI: The Emergence of Economic Rationality of GPT
(This is a joint seminar organised by the Institute of Behavioural and Decision Science (IBDS) and Institute of Digital Economy & Innovation (IDEI).)
Associate Professor,
Department of Economics,
Tsinghua University
Prof. Tracy Xiao Liu is an Associate Professor at the Department of Economics, School of Economics and Management, Tsinghua University. She studies behavioral market design and behavioral game theory, such as the design of innovative markets and transfer of learning between repeated games.
Recently, she is working on the intersection between computer science and economics. This involves collaboration with leading high-tech companies in China such as XuetangX and Tencent.
As large language models (LLMs) like GPT become increasingly prevalent, it is essential that we assess their capabilities beyond language processing. This paper examines the economic rationality of GPT by instructing it to make budgetary decisions in four domains: risk, time, social, and food preferences. We measure economic rationality by assessing the consistency of GPT decisions with utility maximization in classic revealed preference theory. We find that GPT decisions are largely rational in each domain and demonstrate higher rationality scores than those of humans reported in the literature. We also find that the rationality scores are robust to the degree of randomness and demographic settings such as age and gender, but are sensitive to contexts based on the language frames of the choice situations. These results suggest the potential of LLMs to make good decisions and the need to further understand their capabilities, limitations, and underlying mechanisms.
No registration required.
